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    王博

    • 教授     博士生导师   硕士生导师
    • 主要任职:Deputy director of State Key Lab of Structural Analysis for Industrial Equipment
    • 其他任职:工业装备结构分析国家重点实验室副主任
    • 性别:男
    • 毕业院校:大连理工大学
    • 学位:博士
    • 所在单位:力学与航空航天学院
    • 学科:工程力学. 计算力学
    • 办公地点:工程力学系系楼304房间
    • 联系方式:办公电话: 0411-84706608; 手机: 壹叁玖肆贰捌伍玖捌伍伍
    • 电子邮箱:wangbo@dlut.edu.cn

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    Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

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    论文类型:期刊论文

    发表时间:2017-06-01

    发表刊物:APPLIED COMPOSITE MATERIALS

    收录刊物:SCIE、EI

    卷号:24

    期号:3

    页面范围:575-592

    ISSN号:0929-189X

    关键字:Hierarchical stiffened shell; Adaptive equivalent strategy; Fixed point iteration; Multilevel optimization; Asymptotic homogenization method; Buckling

    摘要:In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.